| /* Copyright 2017 The TensorFlow Authors. All Rights Reserved. |
| |
| Licensed under the Apache License, Version 2.0 (the "License"); |
| you may not use this file except in compliance with the License. |
| You may obtain a copy of the License at |
| |
| http://www.apache.org/licenses/LICENSE-2.0 |
| |
| Unless required by applicable law or agreed to in writing, software |
| distributed under the License is distributed on an "AS IS" BASIS, |
| WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| See the License for the specific language governing permissions and |
| limitations under the License. |
| ==============================================================================*/ |
| |
| // Common kernel registrations for XLA devices. |
| |
| #ifndef TENSORFLOW_COMPILER_JIT_XLA_DEVICE_OPS_H_ |
| #define TENSORFLOW_COMPILER_JIT_XLA_DEVICE_OPS_H_ |
| |
| #include "tensorflow/core/framework/op_kernel.h" |
| #include "tensorflow/core/framework/resource_mgr.h" |
| #include "tensorflow/core/kernels/cast_op.h" |
| #include "tensorflow/core/kernels/constant_op.h" |
| #include "tensorflow/core/kernels/control_flow_ops.h" |
| #include "tensorflow/core/kernels/identity_op.h" |
| #include "tensorflow/core/kernels/no_op.h" |
| #include "tensorflow/core/kernels/sendrecv_ops.h" |
| #include "tensorflow/core/kernels/variable_ops.h" |
| |
| namespace tensorflow { |
| |
| // Dummy OpKernel, used for kernels assigned to an XLA device that should be |
| // compiled. Should never be called at runtime since such ops should be |
| // rewritten to a _XlaLaunch op. If it is called, it means the placer placed an |
| // operator on an XLA device but the compiler did not compile it. |
| class XlaDeviceDummyOp : public OpKernel { |
| public: |
| explicit XlaDeviceDummyOp(OpKernelConstruction* ctx); |
| void Compute(OpKernelContext* ctx) override; |
| }; |
| |
| #define REGISTER_XLA_LAUNCH_KERNEL(DEVICE, KERNEL, TYPES) \ |
| REGISTER_KERNEL_BUILDER(Name("_XlaLaunch") \ |
| .Device(DEVICE) \ |
| .HostMemory("constants") \ |
| .HostMemory("resources"), \ |
| KERNEL); |
| |
| #define REGISTER_XLA_DEVICE_KERNELS(DEVICE, TYPES) \ |
| REGISTER_KERNEL_BUILDER(Name("_Send").Device(DEVICE), SendOp); \ |
| REGISTER_KERNEL_BUILDER(Name("_Recv").Device(DEVICE), RecvOp); \ |
| REGISTER_KERNEL_BUILDER( \ |
| Name("_HostSend").Device(DEVICE).HostMemory("tensor"), SendOp); \ |
| REGISTER_KERNEL_BUILDER( \ |
| Name("_HostRecv").Device(DEVICE).HostMemory("tensor"), RecvOp); \ |
| REGISTER_KERNEL_BUILDER( \ |
| Name("_HostCast").Device(DEVICE).HostMemory("x").HostMemory("y"), \ |
| CpuCastOp); \ |
| REGISTER_KERNEL_BUILDER(Name("NoOp").Device(DEVICE), NoOp); \ |
| REGISTER_KERNEL_BUILDER( \ |
| Name("Const").Device(DEVICE).TypeConstraint("dtype", TYPES), \ |
| ConstantOp); \ |
| REGISTER_KERNEL_BUILDER( \ |
| Name("Identity").Device(DEVICE).TypeConstraint("T", TYPES), IdentityOp); \ |
| REGISTER_KERNEL_BUILDER(Name("Placeholder").Device(DEVICE), PlaceholderOp); \ |
| REGISTER_KERNEL_BUILDER(Name("PlaceholderV2").Device(DEVICE), \ |
| PlaceholderOp); \ |
| \ |
| REGISTER_KERNEL_BUILDER( \ |
| Name("VarHandleOp").Device(DEVICE).HostMemory("resource"), \ |
| ResourceHandleOp<Var>); |
| |
| } // namespace tensorflow |
| |
| #endif // TENSORFLOW_COMPILER_JIT_XLA_DEVICE_OPS_H_ |